Instructions to use dipikakhullar/olmo-code-python2-3-tagged with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dipikakhullar/olmo-code-python2-3-tagged with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("allenai/OLMo-1B-hf") model = PeftModel.from_pretrained(base_model, "dipikakhullar/olmo-code-python2-3-tagged") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 700ac44c17e818a182474292000a76d8b1389da0094a3fa783cd700787a22abf
- Size of remote file:
- 16.4 kB
- SHA256:
- 202184bd9cd84d9277cc1c75a1a09eb3a2ebeb6f5a15d5035427351ecaa5ad78
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